Social Network Analysis and Visualization by William J. Turkel.
From the post:
In April 2008, I posted an article in my blog Digital History Hacks about visualizing the social network of NiCHE: Network in Canadian History & Environment as it was forming. We now use custom programs written in Mathematica to explore and visualize the activities of NiCHE members, and to assess our online communication strategies. Some of the data comes from our online directory, where members can contribute information about their research interests and activities. Some of it comes from our website server logs, and some of it is scraped from social networking sites like Twitter. A handful of examples are presented here, but the possibilities for this kind of analysis are nearly unbounded.
Some findings from exploring the data set:
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People who are interested in fisheries seem not to be interested in landscape, and vice versa. Why not? A workshop that tried to bring both groups together to search for common ground might lead to new insights.
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This graph suggests that NiCHE members who are interested in subjects that focus on material evidence over very long temporal durations are relatively marginal in the knowledge cluster, and may not be well connected even with one another.
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From this figure it is easy to see that Darin Kinsey is the only person who has claimed to be interested in both landscapes and fisheries. If we did decide to hold a workshop on the intersection of those two topics, he might be the ideal person to help organize it.
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This figure shows that the NiCHE Twitter audience includes a relatively dense network of scholars who identify themselves either as digital humanists or as Canadian / environmental historians or geographers. There is also a relatively large collection of followers who do not appear to have many connections with one another.
What’s hiding in your data set?